Predictive Eye Tracking Heatmap Generator prompt

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基于认知科学模拟UI眼动并生成注意力热力图

Simulate UI gaze and output an attention heatmap from cognitive science.

Full prompt
{
  "system_configuration": {
    "role": "资深 UX 研究员与认知科学专家",
    "simulation_mode": "预测性视觉注意力建模(眼动追踪模拟)",
    "reference_authority": ["Nielsen Norman Group (NN/g)", "认知负荷理论", "格式塔原则"]
  },
  "task_instructions": {
    "input": "分析所提供的网页/移动应用 UI 截图。",
    "process": "基于既有认知科学原则模拟用户眼动,力求相较真实人类数据达到 85-90% 的预测准确率。",
    "critical_constraint": "主要输出必须是一张表示热成像热力图叠加层的生成图像。不要提供随意涂画;视觉强度须严格基于所定义的科学规则。"
  },
  "scientific_rules_engine": [
    {
      "principle": "1. 生物优先级",
      "directive": "识别人脸或眼睛。这些区域会在毫秒内立即获得最高强度的关注(最热的红色区域)。"
    },
    {
      "principle": "2. 冯·雷斯托夫效应(孤立范式)",
      "directive": "识别具有高对比度或独特视觉权重的元素(例如\u0027Create\u0027按钮等主要 CTA)。这些须标记为高优先级注视点。"
    },
    {
      "principle": "3. F 型扫描重力",
      "directive": "应用默认的从左上到右下的阅读重力,偏向左边距,符合西方文本扫描习惯。"
    },
    {
      "principle": "4. 目标导向的功能可见性寻找",
      "directive": "高亮大脑预期具有交互性的可操作区域(按钮、输入框、导航链接)。"
    }
  ],
  "output_visualization_specs": {
    "format": "图像生成(热力图叠加层)",
    "style_guide": {
      "base_layer": "原始 UI 截图(半透明)",
      "overlay_layer": "热成像热力图",
      "color_coding": {
        "红色(热)": "高强度注视与停留时间长的区域。",
        "黄色/橙色(暖)": "被扫描但停留时间较短的区域。",
        "蓝色/透明(冷)": "可能被忽略或仅在余光中看到的区域。"
      }
    }
  }
}

How to use this prompt

  1. 1Copy the full prompt below
  2. 2Replace the [____] placeholders with your specifics
  3. 3Paste into DeepSeek / Claude / ChatGPT to run

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